Water quality early warning method and system

Abstract

The invention provides a water quality early warning method and system. The method comprises the following steps: acquiring current biological motion characteristic data of a water area to be detected; and inputting the current biological motion characteristic data of the water area to be detected into the water quality early warning model to obtain an early warning result, wherein the water quality early warning model is obtained by training a support vector machine model by adopting a differential evolution algorithm and a grey wolf optimization algorithm. According to the method and the system provided by the invention, the support vector machine model is trained through the differential evolution algorithm and the grey wolf optimization algorithm to obtain the water quality early warning model, the water quality early warning model is used for performing water quality early warning on the water area to be detected, the accuracy of water quality early warning can be improved, and the method and the system have the advantage of high global search capability.

Description

technical field [0001] The invention relates to the field of water quality early warning, in particular to a water quality early warning method and system. Background technique [0002] Water quality is the abbreviation of water quality, which is generally measured by the physical (such as color, turbidity, odor, etc.), chemical (inorganic and organic content) and biological (bacteria, microorganisms, plankton, benthic organisms) of the water body. . At present, with the development of science and technology and the improvement of human living standards, human beings are paying more and more attention to water quality. Water quality early warning has become a hot topic for researchers. [0003] At present, water quality early warning has achieved certain results. According to the characteristic parameters of biological (mainly fish) trajectory, parameter weighted summation or machine learning algorithm is used for biological water quality early warning. However, the metho...

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Problems solved by technology

However, the method of parameter weighted summation requires a large number of experiments to obtain the optimal weight value; while machine learning methods mostly use the SVM (Support Vector Machine, Support Vector Machine) model to perform binary classification on biometric data to obtain early warning results. , however, although the current SVM model and the improved SVM model have good local search capabilities, they have problems of poor stability and low accuracy in global search

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